Dear R Users,
I am happy to announce the initial release (v0.1.3) of lrequire<https://cran.r-project.org/web/packages/lrequire/>, now available on CRAN.
https://cran.r-project.org/web/packages/lrequire/
lrequire supports modularization of R Scripts, enabling encapsulation of information and caching of scripts. This is very similar to the require()<https://nodejs.org/api/modules.html> support in node.js<https://nodejs.org/>.
Use of lrequire encourages separation of responsibility and using modules to encapsulate specific functionality. This leads to more easily-maintained scripts and encourages reuse.
lrequire also cache loaded modules (scripts) such that the next load (source) of the script does not execute its contents, unless specified. For example, if a module is built around sourcing a slowly-changing dataset that is time-consuming to retrieve, frequent reloads of the module will only return the cached copy of the data, saving the time expense. I found this very useful for developing dashboard components – lrequire permitted me the freedom to keep tweaking the UI without having to wait for the live reload of the data.
How It Works
Goal: build a reusable module to welcome an individual. Any environment artifacts necessary to build that module are encapsulated in the lrequire() call and only the functionality is returned.
For example:
________________________________
File: welcome.R
data.that.will.not.be.exposed <- 'some work'
hello <- function(person.name) {
return (paste0('Hello, ', person.name, '!'))
}
module.exports = hello
________________________________
File: main.R
hello <- lrequire(welcome)
hello('Rick')
________________________________
Note that the variable declared in welcome.R will not be visible in main.R only the hello() function. Multiple pieces of information can be exposed by returning a list() object in module.exports. Refer to the documentation for details.
All the best,
Rick Wargo
https://linkedin.com/in/rickwargo/https://www.rickwargo.com/
@rickwargo
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